图2展示了一个CNN编码器以两个图像区域作为输入。我们的目标是以这样一种方式对编码器进行自监督预训练,即学到的表示能够为下游任务如对象检测和实例分割量身定做。 对齐相应区域 (Aligning corresponding regions)。如图2所示,ReSim在图像的两个视图上的子图像级区域上执行自监督相似性学习。给定同一输入图像 I 的...
The convolutional feature maps used by region-based detectors, like Fast RCNN, can also be used for generating region proposals.RPNs are designed to efficiently predict region proposals with a wide range of scales and aspect ratios. Faster R-CNN is composed of two modules,the first module is...
得益于基于anchors的多尺度设计,我们可以像Fast R-CNN detector那样,仅使用一幅单尺度图像计算得到的convolutional features。这里,多尺度anchors是关键,它使得Faster R-CNN能够共享特征而不需要再去解决多尺度的问题。 3. Fast R-CNN object detection network Faster RCNN的第二部分和Fast RCNN中object detction net...
In this paper, we propose a novel method called Rotational Region CNN (R2CNN) for detecting arbitrary-oriented texts in natural scene images. The framework is based on Faster R-CNN [1] architecture. First, we use the Region Proposal Network (RPN) to generate axis-aligned bounding boxes that...
In this work, we introduce a Region Proposal Network(RPN) that shares full-image convolutional features with the detection network, thus enabling nearly cost-free region proposals. 文章是将RPN和 R-CNN做一个共享和融合,从而达到加速的目的。
论文阅读 文章地址 ImageNet Classification with Deep Convolutional Neural Networks 论文阅读 摘要 一、Introduction 1.1 论文贡献 二、ImageNet数据集 三、The Architecture 3.1 **函数 3.2 多种GPU的训练 3.3 本地响应标准化 3.4 重叠池化 3.5 总体结构 四、减少过拟合 4... ...
2) hallucinating visual features with a generative model 3) image-text pretraining 【this paper falls into】 existing paper based on CNN and assume image-text pretrained models are given and focus on finetuning or adaptation. this paper:focuses on improving the upstream image-text pretraining wit...
论文阅读:(CCFR)Re-rank Coarse Classification with Local Region Enhanced Features for FGIR,程序员大本营,技术文章内容聚合第一站。
简介:【PyTorch实战演练】Fast R-CNN中的RoI(Region of Interest)池化详解 0. 前言 按照国际惯例,首先声明:本文只是我自己学习的理解,虽然参考了他人的宝贵见解及成果,但是内容可能存在不准确的地方。如果发现文中错误,希望批评指正,共同进步。 本文基于Ross Girshick在2015年发表的论文Fast R-CNN讲解在FastR-CNN中...
本文基于论文Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks对RPN候选区域网络进行解析说明,并基于PyTorch库对RPN网络进行编程。 创作本文的背景: 在我的专栏【PyTorch实例实战演练】中,已经有了4篇左右文章专门介绍图像分类相关的深度学习模型算法,对这类任务已经比较熟悉了。更进一步地...